Artificial Pancreas Development -- #DData Academic Update

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Automated Insulin Delivery Systems - Academic Update Trang Ly MBBS FRACP PhD Pediatric Endocrinologist, Clinical Assistant Professor Stanford University, Buckingham Group DiabetesMine D-Data Exchange 10 June 2016

Transcript of Artificial Pancreas Development -- #DData Academic Update

Page 1: Artificial Pancreas Development -- #DData Academic Update

Automated Insulin Delivery Systems - Academic Update

Trang Ly MBBS FRACP PhD Pediatric Endocrinologist, Clinical Assistant Professor

Stanford University, Buckingham Group

DiabetesMine D-Data Exchange 10 June 2016

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Disclosures• Investigator for studies sponsored by Medtronic and

Tandem• Co-investigator on studies with:• Boris Kovatchev - University of Virginia• Roman Hovorka - Cambridge University• Edward Damiano - Boston University• Doyle and Dassau - Harvard University• B. Wayne Bequette - Rensselaer Polytechnic Institute

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Design

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Medtronic - Hybrid Closed Loop

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BetaBionics - iLet

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Type Zero - inControl

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Insulin delivery

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

Algorithm PID-IFB Control to range MPC MPC - insulin; PD - glucagon MPC

Dosing Microbolus5 minutes

Basal - 5 minutes, Correction - 1h

Insulin infusion rate - 10 minutes 5 minutes 5 minutes

System calculated meal dosing

Glucagon - 5 minutes

Automated Component

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Initialization

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

TDD - Total daily insulin Basal, I:CHO, ISF Basal, I:CHO, ISF Weight Basal, I:CHO, ISF

Sensor for 48 hours TDD TDD TDD

Basal, I:CHO, ISF Weight Weight

Initialization Parameters

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Setpoint

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

Setpoint 120mg/dL Day: 160mg/dL Treat-to-target: 104-131 mg/dL

Insulin and glucagon setpoint is 100 mg/dL

Day: 80-140 mg/dL

Night: 120mg/dL Optional individual

setpointAdjustable by user up

to 130 mg/dLNight: 90-140 mg/dL

Exercise Temp target - 150mg/dL

Safety: no more than usual basal

Exercise specific setpoint

Setpoint

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Insulin on Board

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

Meals Set by user 2-8h 6h

Basal System derived 4h System derived Insulin clearance 6.5h; Peak 65 minutes

Insulin decay curve depends on glucose:>300 – 2h200-300 - 4h 140-200 - 6h<140 - 8h

Insulin on Board

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Performance

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Comparison• Different settings: free-living vs. monitored• Different hypoglycemia treatment thresholds• Different patient population: A1C, hypoglycemia

awareness

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7:00 8:10 9:20 10:30 11:40 12:50 14:00 15:10 16:20 17:30 18:40 19:50 21:00 22:10 23:20 0:30 1:40 2:50 3:59 5:09 6:190

50

100

150

200

250 Sensor-augmented pump

Hybrid closed-loop

Time

Sens

or G

luco

se -

mg/

dLJDRF Hotel 670G Adolescents

n=15, Mean A1C 9.0%, 70% in range 70-180 mg/dL

Ref - Ly, Weinzimer, Maahs et. al. Pediatric Diabetes 2016

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Ref - Thabit, Hovorka et. al. NEJM 2015

Cambridge Group - 3 monthsAdult n=33, 68% in range 70-180 mg/dL, A1C 7.6% to 7.3%

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Meals

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

I:CHO I:CHO I:CHO Gives 75% of 4h postprandial insulin needed for that meal size and type. First meal-priming bolus is based on the patients weight (0.05u/kg).

If BG <120 or no BG entered, give 80% If BG >120, give 100%

Meals

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Strengths

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

Integrated system124 pts - 3 months

Pivotal trial

13 pts - 6 monthsRemote monitoringSoftware updates

Pump agnostic

33 pts - 3 months 48 pts - 12 daysIntegrated

DesignAdjustable setpoint

Meal adaptation

Run-to-run optimization currently being tested

Strengths

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Challenges

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Medtronic Diabetes University of Virginia Cambridge University Boston University Harvard University

• Managing expectations

• Need remote monitoring

• Adjustable setpoint

• Moving to a commercial platform

• Need to maintain connectivity

• Setpoint may be too high during day

• No commercial partner

• No remote monitoring

• System not integrated

• Glucagon long-term• Design - IOB• Need longer studies

• No commercial partner

• No remote monitoring

• Need longer studies

Challenges

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Summary• Closed-loop therapies will be transformative for

diabetes care• First generation systems will be conservative• Need longer term safety and efficacy trials• Next challenges – • User interface• Human factors • Fail-safe modes

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Thank you

Anirban Roy + Benyamin GrosmanMarc Breton

Ed Damiano + Firas El-KhatibRoman Hovorka

Eyal Dassau

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